Method and system for visualizing abnormal bobbin position of a chemical fiber yarn car based on a three-dimensional model

Abstract

The application discloses a method and system for visual monitoring of abnormal bobbin position of a chemical fiber yarn vehicle based on a three-dimensional model, defines a bobbin position space coordinate to generate a standardized candidate list and automatically binds production data, drives automatic matching and index caching construction of a target node in three-dimensional geometric description data based on a linkage event, updates visual attributes in real time according to state values and batch recovers a final state after interaction ends, realizes automatic mapping and real-time linkage of production data and three-dimensional visual nodes, quickly locates an abnormal bobbin position without manual configuration, can adapt to node structures of different vehicle models, and significantly improves the positioning efficiency of the abnormal bobbin position and the vehicle model adaptation capability of the system.

Description

Technical Field

[0001] This invention relates to the field of industrial mechanism technology, specifically to a method and system for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on three-dimensional models. Background Technology

[0002] In the field of chemical fiber yarn production monitoring, existing technologies typically employ robots to perform yarn bobbin grabbing and placement operations, and use host computer software to record bobbin occupancy status and yarn bobbin production data, while simultaneously using 3D models to visualize the yarn cart. However, existing solutions lack an automatic association mechanism between the visualization nodes of the 3D model and the bobbin position data in the database, often relying on manual configuration of the mapping relationship. Furthermore, updates to abnormal states do not automatically drive visual changes in the corresponding nodes of the 3D model, requiring operators to repeatedly switch between the data list and the 3D view to locate abnormal bobbin positions.

[0003] This disconnect between data and 3D visualization leads to low efficiency in locating abnormal cylinder positions. Furthermore, when the model of the cable car changes or the nodes of the 3D model are adjusted, a tedious manual reconfiguration is required, making it difficult to adapt to the monitoring needs of different models. Summary of the Invention

[0004] This invention aims to provide a method and system for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on three-dimensional models, which significantly improves the positioning efficiency of abnormal bobbin positions and the system's vehicle model adaptability.

[0005] To achieve the above objectives, the technical solution adopted by this invention is: a method for visually monitoring abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model, comprising: Define the spatial coordinates of the tube position and filter available tube positions to generate a standardized candidate list; select the target tube position based on the standardized candidate list, bind the tube production data with the target tube position and write it into storage; listen for abnormal state update requests, update the storage and generate linkage events after verification; respond to the linkage events, match target nodes in the three-dimensional geometric description data and build an index cache; query visual attributes based on the state values ​​in the linkage events and apply them to the target nodes, supporting interactive filtering; detect the interaction end signal, read the latest data to generate a final state attribute snapshot and batch restore the node visual state.

[0006] Preferably, the step of defining the spatial coordinates of the cylinder positions and filtering available cylinder positions to generate a standardized candidate list includes: establishing a three-dimensional rectangular coordinate system and assigning a unique position code to each cylinder position; reading all cylinder position status information to form a complete cylinder position status set; removing occupied, abnormal, and blacklisted cylinder positions based on the complete cylinder position status set to obtain a set of valid available cylinder position candidates; and sorting the set of valid available cylinder position candidates in ascending row and column order to output a standardized candidate list.

[0007] Preferably, selecting a target bobbin position based on the standardized candidate list and binding the bobbin production data with the target bobbin position to write it into storage includes: selecting a target bobbin position from the standardized candidate list according to a preset allocation mode; collecting bobbin production data and combining it with the target bobbin position and the bobbin machine number to form a data record; writing the data record into storage using the combination of the bobbin machine number and the target bobbin position as the primary key; and generating and sending robot operation instructions based on the target bobbin position and its spatial coordinates.

[0008] Preferably, the process of listening for abnormal status update requests, updating storage and generating linkage events after successful verification includes: receiving abnormal status update requests and performing correlation verification based on data records; updating the abnormal status field of the corresponding record in storage to a new status value after successful verification; generating a linkage event containing the silk car number, bobbin position code and new status value based on the updated data snapshot; writing the linkage event into an event queue and sending an event ready notification.

[0009] Preferably, the step of responding to the linkage event by matching target nodes in the 3D geometric description data and constructing an index cache includes: loading the 3D geometric description data and parsing it to obtain a list of original node names; generating target node names according to naming rules based on the spool code in the linkage event and matching them in the list of original node names; writing the successfully matched node references and the spool code as key-value pairs into an in-memory hash table to construct an index cache; performing a mapping integrity check based on the index cache and the data records in storage and outputting valid node references.

[0010] Preferably, visual attributes are queried based on the state value in the linkage event and applied to the target node, supporting interactive filtering, including: querying the configuration table using the new state value in the linkage event as an index to determine the target rendering parameters; applying the target rendering parameters to the node pointed to by the valid node reference and triggering a local redraw; receiving filtering instructions and calculating the node visibility mask based on the data records in storage; adjusting the node display state according to the node visibility mask and supporting reverse querying of data records by clicking on the node.

[0011] Preferably, the step of detecting the end signal of the interaction, reading the latest data to generate a final state attribute snapshot and batch restoring the visual state of the nodes includes: triggering the recovery process and pausing event listening when a filtering cancellation or view switching signal is detected; rereading all data records and querying according to the configuration table to generate a set of final state attribute snapshots; traversing the set of final state attribute snapshots and obtaining node references through the index cache to batch apply the final state attributes; performing a final state consistency check and sending a recovery completion signal to restart event listening after passing the check.

[0012] Preferably, selecting a target cylinder position from the standardized candidate list according to a preset allocation mode includes: selecting the first element in the standardized candidate list as the target cylinder position in a sequential allocation mode or a row-priority allocation mode; rearranging the standardized candidate list in column-priority allocation mode by ascending column number and row number and then selecting the first element as the target cylinder position; if the standardized candidate list is empty, terminating the allocation and generating an alarm message.

[0013] Preferably, the process of receiving an abnormal status update request and performing correlation verification based on the data record includes: querying whether there is a record in the storage with the yarn car number and bobbin position code in the request as the primary key; if there is, further verifying whether the yarn bobbin number in the record is consistent with the yarn bobbin number provided by the request source; accepting the abnormal status update request and entering the update process only when both verifications pass; and recording an abnormal log and discarding the abnormal status update request when the verification fails.

[0014] On the other hand, this invention proposes a visual monitoring system for abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model, comprising: The candidate set construction unit is used to define the spatial coordinates of the cylinder and filter available cylinders to generate a standardized candidate list. A data binding unit is used to select a target bobbin position based on the standardized candidate list and bind the bobbin production data with the target bobbin position and write it into storage. The event generation unit is used to listen for abnormal status update requests, update the storage and generate related events after verification; A node mapping unit is used to respond to the linkage event, match target nodes in the three-dimensional geometric description data, and build an index cache; The visual update unit is used to query visual attributes based on the state values ​​in the linkage event and apply them to the target node, supporting interactive filtering. The state recovery unit is used to detect the end signal of the interaction, read the latest data to generate a snapshot of the final state attributes, and restore the visual state of the nodes in batches.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention generates a standardized candidate list by defining the spatial coordinates of cylinder positions and automatically binds it to production data. Based on the linkage event-driven automatic matching and index caching of target nodes in the 3D geometric description data, it updates visual attributes in real time according to the state value and restores the final state in batches after the interaction ends. This realizes the automatic mapping and real-time linkage between production data and 3D visualization nodes. It can quickly locate abnormal cylinder positions without manual configuration, and can also adapt to the node structure of different vehicle models, significantly improving the efficiency of abnormal cylinder position location and the vehicle model adaptability of the system. Attached Figure Description

[0016] Figure 1This is a flowchart of the present invention: a visual monitoring method for abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model. Figure 2 This is a block diagram of the abnormal bobbin position visualization monitoring system for chemical fiber filament carts based on a three-dimensional model, as described in this invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a specific posture. If the specific posture changes, the directional indicators will also change accordingly.

[0019] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the use of "and / or" or "and / or" throughout the text includes three parallel solutions. For example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0020] Please see Figure 1 This invention provides a method for visually monitoring abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model, comprising: Define the spatial coordinates of the cylinder locations and filter available cylinder locations to generate a standardized candidate list; specifically including: Establish a three-dimensional rectangular coordinate system and assign a unique position code to each cylinder position; read all cylinder position status information to form a complete cylinder position status set; based on the complete cylinder position status set, remove occupied, abnormal, and blacklisted cylinder positions to obtain a set of valid and usable cylinder positions; sort the set of valid and usable cylinder positions in ascending order of row number and column number and output a standardized candidate list.

[0021] By constructing a unified three-dimensional spatial coding system and combining it with multi-dimensional state filtering and standardized sorting, the system achieves automated and accurate screening and orderly output of available cylinder positions. This avoids the risk of misselection caused by manual judgment of cylinder position availability and provides a standardized data foundation for the automatic selection of subsequent target cylinder positions, thereby improving the efficiency and accuracy of cylinder position allocation.

[0022] Target bobbin positions are selected based on a standardized candidate list, and bobbin production data is bound to these target bobbin positions and written into storage; specifically, this includes: Select the target bobbin position from the standardized candidate list according to the preset allocation mode; collect bobbin production data and combine it with the target bobbin position and bobbin number to form a data record; write the data record into storage using the combination of bobbin number and target bobbin position as the primary key; generate robot operation instructions based on the target bobbin position and its spatial coordinates and send them.

[0023] The process of selecting a target cell from a standardized candidate list according to a preset allocation mode includes: selecting the first element in the standardized candidate list as the target cell in either a sequential allocation mode or a row-priority allocation mode; reordering the standardized candidate list in ascending column and row order in a column-priority allocation mode and then selecting the first element as the target cell; and terminating the allocation process and generating an alarm message if the standardized candidate list is empty.

[0024] By supporting multiple preset allocation modes to flexibly select target bobbin positions and binding production data with composite primary keys, the bobbin position allocation strategy is configurable and the data storage is structured. This not only meets the personalized allocation needs under different production line layouts, but also ensures the unique correspondence between bobbin production data and physical bobbin positions. At the same time, the linkage generates robot operation instructions, realizing a seamless connection from data binding to physical execution, which improves the flexibility and reliability of production scheduling.

[0025] Listen for abnormal status update requests, update the storage and generate a linked event after successful verification; specifically including: Receive an abnormal status update request and perform correlation verification based on the data record; after the verification is successful, update the abnormal status field of the corresponding record in the storage to the new status value; generate a linkage event containing the silk car number, the tube position code and the new status value based on the updated data snapshot; write the linkage event to the event queue and send an event ready notification.

[0026] The process of receiving abnormal status update requests and performing correlation checks based on data records includes: querying the storage to see if there is a record with the yarn car number and bobbin position code in the request as the primary key; if it exists, further verifying whether the bobbin number in the record is consistent with the bobbin number provided by the request source; accepting the abnormal status update request and entering the update process only when both checks pass; and recording the abnormal log and discarding the abnormal status update request when the check fails.

[0027] The dual correlation verification mechanism is adopted to ensure the legitimacy and data consistency of the abnormal state update request, effectively preventing dirty data writing caused by misoperations or illegal requests. Meanwhile, the verified update is converted into a standardized linkage event and notified asynchronously, which realizes the safe and controllable change of the abnormal state and the timely triggering of downstream visual responses, and ensures the accuracy of monitoring data and the stability of system operation.

[0028] Respond to the linkage event, match the target node in the 3D geometric description data and construct an index cache; specifically include: Load the 3D geometric description data and parse it to obtain the original node name list; generate the target node name according to the naming rule based on the cylinder position code in the linkage event and perform matching in the original node name list; write the successfully matched node reference and the cylinder position code into the in-memory hash table as a key-value pair to construct the index cache; perform mapping integrity verification based on the index cache and the data records in the storage, and output valid node references.

[0029] The 3D nodes are automatically matched through the naming rule and the in-memory index cache is constructed, which realizes the dynamic and automatic association between the cylinder position codes and the 3D visualization nodes, avoids the cumbersome operation of manually configuring the mapping relationship, and ensures the accuracy of the association result with the help of mapping integrity verification, significantly improving the real-time performance of the abnormal state-driven 3D model response and the system's adaptive ability to the node structures of different vehicle models.

[0030] Query the visual attributes according to the state value in the linkage event and apply them to the target node to support interactive filtering; specifically include: Use the new state value in the linkage event as an index to query the configuration table to determine the target rendering parameter; apply the target rendering parameter to the node pointed to by the valid node reference and trigger local redrawing; receive the filtering instruction and calculate the node visibility mask based on the data records in the storage; adjust the node display state according to the node visibility mask and support clicking the node to query the data record in reverse.

[0031] By dynamically mapping the state values to visual attributes and supporting interactive filtering and reverse query based on data records, real-time two-way linkage between the 3D visualization interface and the back-end production data is realized, enabling operators to intuitively perceive the abnormal state change of the cylinder position and focus on the concerned objects as needed, and trace the complete data record by clicking the node, which significantly improves the information expression efficiency of the monitoring interface and the human-computer interaction experience.

[0032] Detect the interaction end signal, read the latest data to generate a final state attribute snapshot, and restore the visual state of nodes in batches; specifically include: When a filter cancellation or view switching signal is detected, the recovery process is triggered and event listening is paused; all data records are reread and a final state attribute snapshot set is generated by querying the configuration table; the final state attribute snapshot set is traversed and node references are obtained through the index cache and applied in batches; a final state consistency check is performed and a recovery completion signal is sent after passing the check to restart event listening.

[0033] By batch restoring the visual state of nodes and performing final state consistency verification at the end of the interaction, the 3D visualization interface can accurately return to the real rendering state of the full data after filtering or view switching, avoiding display deviations caused by residual local updates. At the same time, the mechanism of pausing and restarting event listening is adopted to prevent state conflicts during the restoration process, ensuring the integrity of the visualization display and the stability of system operation.

[0034] On the other hand, this invention proposes a visual monitoring system for abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model, such as... Figure 2 As shown, it includes: The candidate set construction unit is used to define the spatial coordinates of the cylinder and filter available cylinders to generate a standardized candidate list. A data binding unit is used to select a target bobbin position based on the standardized candidate list and bind the bobbin production data with the target bobbin position and write it into storage. The event generation unit is used to listen for abnormal status update requests, update the storage and generate linked events after verification; A node mapping unit is used to respond to the linkage event, match target nodes in the three-dimensional geometric description data, and build an index cache; The visual update unit is used to query visual attributes based on the state values ​​in the linkage event and apply them to the target node, supporting interactive filtering. The state recovery unit is used to detect the end signal of the interaction, read the latest data to generate a snapshot of the final state attributes, and restore the visual state of the nodes in batches.

[0035] Furthermore, each unit in the above system, during execution, is also used to implement other steps of the above-mentioned method for visual monitoring of abnormal bobbin positions in chemical fiber carts based on three-dimensional models, as follows: Step 1: Define the spatial coordinates of the chemical fiber filament canister and construct the available candidate set; This step aims to establish a standardized spatial description system for the positions of the fiber filament cart bobbins and, based on real-time status, select a set of effective bobbin positions suitable for robot grasping and placement operations, providing a standardized input data foundation for subsequent target bobbin position calculations. As the physical carrier of the fiber bobbins, the fiber filament cart has a fixed row and column structure for its bobbin positions. Only by converting the physical bobbins into calculable numerical spatial coordinates can automated allocation and data association be achieved. Therefore, this step is a prerequisite for the entire monitoring method and specifically includes: Step 1.1: Define the three-dimensional spatial coordinate system and position coding rules for the yarn cart positions. Establish a three-dimensional rectangular coordinate system with the lower left corner of the yarn cart chassis as the origin. The X-axis extends horizontally along the length of the yarn cart, the Y-axis extends vertically along the height of the yarn cart, and the Z-axis extends horizontally along the width of the yarn cart. The three coordinate axes are perpendicular to each other and all have millimeters as their unit of measurement. For any given position, its spatial location is uniquely determined by a triplet (x, y, z), where x represents the coordinate value of the center point of the position along the X-axis, y represents the coordinate value of the center point of the position along the Y-axis, and z represents the coordinate value of the center point of the position along the Z-axis. Simultaneously, assign a unique position code to each position. Where r represents the row number, ranging from 1 to R, and R is the total number of rows on the spinning wheel; c represents the column number, ranging from 1 to C, and C is the total number of columns on the spinning wheel. There is a fixed mapping relationship between the position code and the spatial coordinates, that is, given the position code... The corresponding (x, y, z) coordinate values ​​can be calculated using preset row and column spacing parameters. This mapping relationship is fixed when the yarn train leaves the factory and does not change with the operating status. This spatial coordinate system and position encoding rules provide a unified numerical description benchmark for all subsequent yarn position operations, enabling the physical yarn position to be recognized and processed by the computer.

[0036] Step 1.2: Read all bobbin position status information of the yarn train and initialize the candidate set. Based on the position encoding rules defined in Step 1.1, traverse all R×C bobbin positions of the yarn train and read the real-time status information of each bobbin position from local storage or the host computer interface. The initial status information of each bobbin position includes four attributes: position encoding. Occupancy mark Silk car status indicator V, blacklist indicator .

[0037] Among them, the occupancy mark The value is 0 or 1, where 0 indicates that no yarn spool is currently placed at that position, and 1 indicates that a yarn spool has been placed; the yarn trolley status flag V is 0 or 1, where 0 indicates that the yarn trolley is in normal operation, and 1 indicates that the yarn trolley is in maintenance or locked state; blacklist flag. The value is either 0 or 1, where 0 indicates that the cylinder location is not on the prohibited list, and 1 indicates that it is on the prohibited list. The status information of all cylinder locations is then aggregated to form a complete cylinder location status set. This set contains a complete snapshot of the status of all bobbins on the spinning wheel, serving as the original data source for subsequent screening operations. Its completeness directly determines the accuracy of the candidate set.

[0038] Step 1.3: Generate a valid and usable candidate set of cylinder positions based on multiple filtering conditions. This is based on the full set of cylinder position states obtained in Step 1.2. For input, apply a triple filtering condition to remove unusable cylinder positions. The first filtering step removes occupied positions. The first layer of filtering removes positions where bobbins are already in place, meaning these positions are no longer allocated. The second layer filters bobbins with the bobbin status flag V=1, meaning all bobbins on the bobbin are unavailable when the bobbin is under maintenance or locked. The third layer filters bobbins marked with a blacklist. Cylinder locations marked as disabled by manual or system methods are not included in the allocation. After triple filtering, the remaining cylinder locations constitute a valid candidate set of available cylinder locations. .like If the set is empty, it is determined that there are no available bobbin positions on the current yarn cart, the subsequent allocation process is terminated, and an alarm message indicating no available bobbin positions is generated; if If the result is not empty, it is passed as output to the next step. This candidate set contains only cylinder positions that can actually be placed, avoiding invalid calculations and incorrect assignments. Its generation process is entirely based on objective state flags and does not contain any subjective judgments or empirical rules.

[0039] Step 1.4: Sort the valid candidate set and output a standardized candidate list. This is based on the valid and usable cylinder candidate set obtained in Step 1.3. For input, encoded according to position The candidate positions are sorted in ascending order by row number r and column number c to form an ordered, standardized candidate list. Where k is the number of candidate centralized locations, and satisfies ,when Timely satisfaction This ordered list preserves the spatial topology of the cylinders, allowing subsequent steps to use it directly without reordering when performing sequential, row-major, or column-major allocations. Each element in the list contains only a position code. This standardized candidate list, free of redundant information, ensures the simplicity of data transmission. It is the final output of step one, providing a strictly ordered input sequence for subsequent target cylinder location calculations, thus ensuring the predictability and reproducibility of the allocation results.

[0040] Step 2: Link and bind the target bobbin position calculation with the bobbin production data; This step uses the standardized candidate list output in step one. For direct input, a target bobbin position is selected according to preset allocation rules, and the production data of the bobbin to be placed is uniquely bound to this target bobbin position, forming a traceable data record. This step follows the set of available bobbin positions built in step one, transforming the abstract candidate list into specific operation instructions and data associations, and is the core link connecting physical operations and information management. Without the ordered candidate list provided in step one, this step cannot determine the allocation range, nor can it guarantee the rationality of the allocation result, specifically including: Step 2.1: Select target locations from the candidate list based on the allocation pattern. The standardized candidate list output in Step 1.4 is used as an example. As input, select a target cylinder position based on the currently set allocation mode. There are three allocation modes: sequential allocation, row-major allocation, and column-major allocation. All three modes are based on... The operation is carried out in an orderly manner.

[0041] In sequential allocation mode, select directly. The first element in the middle is as ,Right now In row-major allocation mode, traverse Select the element with the smallest row number and the smallest column number as ,because The elements have already been sorted in ascending row and column order; this operation is equivalent to selecting the first element. In column-first allocation mode, it is necessary to... After re-sorting by column number in ascending order and then by row number in ascending order, select the first element as... Regardless of the mode used, the selected Must belong to That is, it must be one of the usable cylinder positions selected in step one. If If the result is empty, this step cannot be executed, and you must return to step one to retrieve the candidate list again or terminate the process. This step transforms the candidate set from step one into a single target, providing a clear object for subsequent data binding.

[0042] Step 2.2: Collect production data of the bobbin to be placed and construct data records. (This is based on step 2.1, which determines the target bobbin position.) Simultaneously, production data for the currently placed yarn spools is collected from the yarn spool conveyor line or upstream management system. The production data includes six fields: Yarn Spool Number (LNO), Yarn Spool Weight (W) (in kilograms), Batch Number (BatchNo), and Production Time. (Unit: seconds) Abnormal Status (Initial value 0, indicating normal operation), Update time (Unit: seconds). Match the above six fields with the target cylinder position selected in step 2.1. The combination of the silk car number CarId and its corresponding number forms a complete data record: This record uses a combination of the spinning wheel number and the tube location code as its unique primary key, ensuring the uniqueness of each record in the database. The construction of this data record depends entirely on the target tube location determined in step 2.1; if the target tube location is not determined, the data record cannot be generated.

[0043] Step 2.3: Write the data records to storage and complete the association binding. This uses the data records constructed in Step 2.2. As input, it is written to a local database or distributed storage system. Before writing, it is first checked whether the input already exists in the storage. For records with primary keys: if they do not exist, perform an insert operation and... Store it as a new record; if it already exists, perform an update operation. LNO, W, BatchNo, , , The field overwrites the existing record's field with the same name, and... Update to the current timestamp. After the write operation is complete, the yarn production data and target yarn position will be updated. The association binding is now complete. Afterwards, you can query... The primary key allows you to retrieve all production information for the yarn bobbin at that location. This binding relationship is the data foundation for subsequent anomaly synchronization and 3D visualization. If the binding fails, subsequent steps will be unable to obtain the production data corresponding to the yarn bobbin location, and the entire monitoring chain will be interrupted.

[0044] Step 2.4: Send the target cylinder positioning command to the robot actuator. This is based on the target cylinder position selected in Step 2.1. and the spatial coordinates of the cylinder as defined in step 1.1 The input is used to generate robot grasping and placement operation instructions. The instructions include the target cylinder position code. Target space coordinates The command specifies the operation type (placement) and the spool number (LNO). This command is sent to the robot controller via the industrial communication bus. The robot controller then drives the robotic arm to move to the designated position based on the coordinate values ​​to perform the spool placement action. Once the command is sent, this step ends, and... , The operation completion signal is then transmitted as an output to step three. This step transforms the allocation result at the information level into an execution action at the physical level, completing the conversion from data to a physical object. Its execution prerequisite is that steps 2.1 to 2.3 have been successfully completed; otherwise, the robot will not be able to obtain the correct target position and associated data.

[0045] Step 3: Synchronization of abnormal states and generation of visual linkage events; This step records the data output from step two. The system takes the operation completion signal as input, continuously monitors changes in the abnormal state of the wire drum, and generates standardized linkage events when the state changes, providing trigger signals and data content for subsequent 3D visualization updates. This step builds upon the data binding relationship established in step two, transforming static data records into a dynamic event stream, specifically including: Step 3.1: Listen for multi-source abnormal status inputs and verify data relevance. Take the data record written into the storage in step 2.3 as the listening object , and continuously receive abnormal status update requests from manual detection terminals, manufacturing execution systems, quality management systems, and third-party interfaces. Each update request contains three items: yarn vehicle number , bobbin position code , and new abnormal status value .

[0046] After receiving the request, relevance verification is performed first: query whether a record with as the primary key exists in the storage; if it does not exist, the request is determined to be invalid, an abnormal log is recorded and the request is discarded; if it exists, further verify whether the LNO in the record is consistent with the yarn bobbin number provided by the request source, and if they are inconsistent, the request is also determined to be invalid and a log is recorded. This verification process ensures the accuracy of abnormal status updates and prevents incorrect statuses from being written due to misoperations or data disorders.

[0047] Step 3.2: Update the abnormal status field in the storage and record the change time. Taking the update request that passed the verification in step 3.1 as input, the abnormal status field of the corresponding record in the storage is updated to , and the update time field is updated to the current timestamp . The update operation adopts an atomic write method to ensure the consistency of the status value and the timestamp, avoiding the situation where the status is updated but the timestamp is not updated, or vice versa. After the update is completed, the complete content of the record is read, including , , LNO, W, BatchNo, , , , which is used as the data snapshot after the change . This data snapshot contains all the context information of the abnormal status change, and is the complete data basis for generating subsequent linkage events. If the update operation fails, roll back to the pre-update status, record an error log, and do not generate a linkage event to ensure the consistency between the event and the data.

[0048] Step 3.3: Generate a standardized linkage event based on the status change. Taking the changed data snapshot obtained in step 3.2 as input , a standardized linkage event is generated . The event contains five fields: event type Type (fixed as status change), yarn vehicle number , bobbin position code ​New abnormal state values Change timestamp The generation of events follows a unified format specification, regardless of the source of the abnormal state; all state changes from all sources generate events with the same structure. If no state change occurred in step 3.2 (i.e....), the event will be terminated. With the original If the events are the same, no event will be generated to avoid invalid events triggering subsequent visualization updates.

[0049] Step 3.4: Publish the linked event to the event queue and pass it to the next step. This uses the linked event generated in Step 3.3. As input, it is written to the event queue in memory. The event queue manages events using a first-in, first-out (FIFO) principle, ensuring that the processing order of events matches their generation order. After being written to the queue, an event ready notification is sent to step four, including the event's position in the queue. Upon receiving the notification, step four retrieves the event from the queue. Processing begins. If the queue is empty or event writing fails, no notification is sent, and step four will remain in a waiting state until a new event is enqueued. This step completes the temporary storage and transmission of events, ensuring that events are not lost and can be consumed in an orderly manner by subsequent steps.

[0050] Step 4: Automatic mapping of 3D model nodes and construction of index cache; This step is published to the event queue as step 3.4. Linked events To trigger input, upon receiving an event ready notification, the event content is retrieved from the queue and processed based on the silk car number contained within the event. With tube position coding The system automatically locates the corresponding visualization nodes within the loaded 3D geometric description data and simultaneously establishes a persistent index cache for subsequent fast queries. This step follows the standardized linkage events generated in step three, transforming abstract data change signals into concrete 3D spatial object references. It is the core transformation step for achieving data-driven visualization and specifically includes: Step 4.1: Load standardized 3D geometric description data and parse the node tree structure. During system initialization or after receiving the event readiness notification from Step 3, first load the data related to the silk car number from local storage or network services. The corresponding standardized 3D geometric description file. This file is stored in an open standard binary or text format, and internally organizes all visualization nodes in a tree-like hierarchical structure, with each node containing a unique name field. Transformation matrix field Geometric data reference fields and material reference field After loading, traverse the entire node tree and extract the name field of all leaf nodes. This forms the original list of node names. , where m is the total number of leaf nodes in the 3D description data of the silk-cart. This list contains the identifiers of all independently operable visual units in the 3D space and serves as the search space for subsequent matching operations.

[0051] Step 4.2: Generate target node names based on naming rules and perform string matching. This is based on the linked events extracted in Step 3.4. Inner tube coding As input, generate the target node name according to preset naming and concatenation rules. The splicing rule is a fixed prefix followed by the tube position code. direct connection, i.e. ,in This indicates a string concatenation operation, where Prefix is ​​a pre-configured constant string (such as pos). Use the row and column encoding format defined in step one (e.g., r3c5).

[0052] generate Then, the list of original node names obtained in step 4.1 Perform an exact string match search. If an element that is exactly equal to the original is found, record the index of that element in the list. and a complete reference to the corresponding node If no match is found, a mapping failure flag is recorded. and will include failure information (including , , Write to the exception log, but do not interrupt the process; only skip the visual update of the current event.

[0053] Step 4.3: Build a node index cache and write it to an in-memory hash table. This is done using the node references that were successfully matched in Step 4.2. and its corresponding cylinder code For key-value pairs, write them to a hash table in memory. The keys in a hash table are composite primary keys. The value is a node reference. Pre-write checks The system checks if a duplicate key already exists: if it does, the new reference overwrites the old value; otherwise, a new entry is inserted. This hash table resides in memory during system operation, and its lifecycle is consistent with the monitoring process. The purpose of building the cache is to transform the time-consuming string matching operation in step 4.2 into a constant-time lookup operation in subsequent steps. The key structure of the cache is consistent with the primary key structure of the data records in step two, ensuring a unified addressing method between the data layer and the visualization layer.

[0054] Step 4.4: Perform mapping integrity verification and output valid node references. This is done using the hash table updated in Step 4.3. The complete set of data records written to storage in step 2.3 is used as input to perform mapping integrity verification.

[0055] The verification logic is as follows: traverse the storage of the silk cart. Check the existence of the composite primary key for each of the bound spool codes. In the middle, count the number of missing items. Total number of bindings .like If so, a verification alarm message will be generated, listing all missing cylinder position codes, indicating a possible problem of missing 3D data nodes or inconsistent naming; if If the verification passes, then the validation is successful. Regardless of the validation result, as long as the current event in step 4.2 matches successfully, then... The valid output of this step is passed to step five. This verification mechanism ensures global consistency between the data layer and the visualization layer, promptly detects and reports configuration errors, but its execution does not block the processing flow of the current event, ensuring the continuity of real-time monitoring. The output... It carries a precise object reference in three-dimensional space to the location indicated by the event in step three, providing a direct target for the next step of visual attribute updates.

[0056] Step 5: Visual state attribute update and interactive filtering control; This step uses the valid node references output in step 4.4. and the linked events generated in step 3.3 New abnormal state values ​​in For direct input, modify according to the preset state-visual attribute correspondence. The rendering parameters of the pointed-to 3D node are dynamically adjusted in response to user interaction commands, affecting node visibility and display style. This step builds upon the node references and event data established in step four, transforming abstract state values ​​into visually perceptible changes. It is the final execution step for intuitively locating abnormal locations, specifically including: Step 5.1: Query the status-visual attribute mapping configuration and determine the target rendering parameters. This is based on the linked events in Step 3.3. New abnormal state value As an index, query the corresponding combination of visual attributes from the pre-configured table. The configuration table uses status values ​​as keys and visual attribute tuples as values. Each tuple contains four parameters: basic color. (RGB triplet, each component ranges from 0 to 255), transparency (Value range 0.0 to 1.0), High brightness intensity (Value range 0.0 to 2.0), flashing frequency (Unit: Hertz, 0 indicates no flicker).

[0057] For example: when (Normal) time, ; when (When an early warning is issued) ; when (Abnormal) time, .

[0058] Query results This is the target rendering parameter set required for the current event. This configuration table is independent of 3D data and business data, supports runtime hot reloading and updates, and can adjust visual performance without restarting. This step translates the numerical state from step three into executable rendering instructions in step five, completing the first semantic-to-visual conversion.

[0059] Step 5.2: Apply rendering parameters to the node and trigger a local redraw. Use the valid node references output in Step 4.4. and the visual attribute combinations obtained from step 5.1 As input, modify sequentially. The four rendering properties of the pointed-to 3D node: Set the base color to Set the transparency to High brightness intensity set to The blinking animation frequency is set to Attribute modifications are submitted in batches, packaging all changes into a single rendering command and sending it to the graphics rendering pipeline. This avoids frame rate fluctuations caused by multiple individual submissions. After submission, the rendering pipeline only processes the changes. The affected local area will be redrawn, without triggering a full scene reconstruction or a complete data re-read. If If the result is empty due to the failure of mapping in step four, this step is skipped and no rendering operation is performed.

[0060] Step 5.3: Receive user interaction filtering instructions and calculate node visibility masks. Using the 3D scene rendered and updated in Step 5.2 as the interaction object, continuously listen for filtering instructions issued by the user through the input device. Filtering instructions contain one or more filtering conditions, each specifying an attribute field and its expected value set, such as an abnormal state equal to 2, a batch number belonging to a certain list, or a production time within a certain interval. Upon receiving the instruction, iterate through all data records of the silk reel stored in Step 2.3, checking each record one by one to see if it meets all filtering conditions, and generate a Boolean visibility mask array. Where n is the total number of positions on the silk reel. This indicates that the node corresponding to the i-th cylinder position should remain visible. This indicates whether the element should be hidden or semi-transparent. The calculation of the mask array is entirely based on the production data bound in step two, and is independent of the 3D nodes themselves, ensuring consistency between the filtering logic and the business data. This step transforms the user's abstract query intent into specific node visibility control signals, providing a filtered target set for the next step of bidirectional linkage.

[0061] Step 5.4: Apply visibility masks and support reverse data lookups. Use the visibility mask array generated in Step 5.3. and the hash table constructed in step 4.3 For input, iterate through Each element in: For The position of the cylinder, from Get its node reference and the node's opacity. Set to 0.1 or set the visibility flag to false; for The cylinder nodes are then restored to their original rendering parameters set in step 5.2. After application, the scene only highlights the cylinder nodes that meet the filtering criteria.

[0062] Simultaneously, it monitors user clicks on visible nodes: when a user clicks on a node, it... Reverse lookup of the tube position code corresponding to this node , and then Read the complete data record from the storage in step two using the primary key. And display LNO, W, BatchNo, and BatchNo in the sidebar or pop-up window. , , All fields. This two-way linkage enables seamless backtracking from three-dimensional space to business data. Its feasibility depends entirely on the data binding established in step two and the node caching established in step four. Together, the three form a complete visual interaction loop.

[0063] Step Six: Data Consistency Final State Verification and Model State Restoration; This step takes the 3D scene and data storage state after the interactive filtering and reverse query completed in step 5.4 as input. When the user cancels filtering or switches the spinning car view, it performs a final state check of global data-node consistency, and restores the visual attributes of all 3D nodes to the final state that is strictly consistent with the current database state, ensuring that there are no residual temporary filtering effects or outdated states on the interface, which specifically includes: Step 6.1: Detect the filtering cancellation or view switching signal and trigger the restoration process. Continuously monitor the user interaction event stream. When an instruction to close the filtering panel, clear the filtering conditions, or switch the spinning car view is detected, it is determined that the current interaction session is ended, and the state restoration process is triggered immediately. The trigger signal includes the current spinning car number and the restoration mode flag (0 indicates cancel filtering restoration, 1 indicates view switching restoration). The detection of this signal is completely based on the interaction monitoring channels established in steps 5.3 and 5.4, reusing the same event bus without introducing additional monitoring overhead. After triggering, the reception of new linkage events is paused until the restoration process is completed, so as to avoid race conditions between new events and restoration operations during the restoration process. This step ensures the timing accuracy of the restoration operation, and prevents interface flickering or state disorder caused by mistakenly triggering restoration while the user is still interacting.

[0064] Step 6.2: Reread the full amount of data records and generate a final state attribute snapshot. Taking the data in the trigger signal of step 6.1 as input, read the latest data record set of all bound bobbin positions under this spinning car from the storage in step 2.3 . For each record in, extract its abnormal status field , and query the corresponding visual attribute combination according to the same configuration table in step 5.1 to generate a final state attribute snapshot set: . This snapshot set represents the correct visual state that all bobbin positions in the database should have at the current moment, and is the authoritative benchmark for restoration operations. The snapshot generation process completely reuses the attribute query logic of step 5, ensuring that the restored state is completely visually consistent with the state of normal linkage update, avoiding the situation where the restored color or flicker frequency does not meet expectations.

[0065] Step 6.3: Traverse the hash table and apply the final state attributes to all nodes in batches. Taking the final state attribute snapshot set generated in step 6.2 and the hash table constructed in step 4.3 as input, traverse each element in: using as the key from to obtain the node reference If the reference is valid, then the corresponding step in step 6.2 will be used. Batch apply to this node, overriding any temporary transparency or hidden state that may have been set in step 5.4; if the reference is invalid (i.e. If no corresponding entry is found, a missing log entry is recorded, but the traversal is not interrupted. All node attribute modifications are also committed in batches to ensure that the recovery operation is completed within a single frame, avoiding visual tearing caused by node-by-node updates.

[0066] Step 6.4: Perform final state consistency verification and output a recovery completion signal. This is based on the 3D scene after batch attribute application in Step 6.3 and the final state attribute snapshot set from Step 6.2. As input, perform a final state consistency check. The check logic is: randomly sample... Read the current rendering attributes of at least 10% of the sample nodes and compare them with... The expected attributes recorded in the data are compared item by item, and the number of inconsistencies is counted. .like If the verification passes, a recovery completion signal is generated. And reopen the event listening channel from step three, allowing new linked events to enter the processing flow; if If the verification fails, detailed inconsistency information (including node name, expected attribute, and actual attribute) is recorded, and a recovery exception alarm is generated, but the error message is still sent. This releases the event listening pause state, preventing permanent system blocking. This final state verification supplements the initial mapping verification in step 4.4, specifically addressing interactive recovery scenarios to ensure the system state remains reliable even after prolonged operation and frequent interactions. The output... This marks the complete end of the current monitoring session or view switch, and the system returns to standby mode, ready to respond to the linkage events generated in the next step.

[0067] The above description is merely an exemplary embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention specification and drawings under the technical concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for visually monitoring abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model, characterized in that, include: Define the spatial coordinates of the cylinder location and filter available cylinder locations to generate a standardized candidate list; Based on the standardized candidate list, a target bobbin position is selected, and the bobbin production data is bound to the target bobbin position and written into storage. Listen for abnormal status update requests, update the storage and generate a related event after successful verification; In response to the linkage event, target nodes are matched in the three-dimensional geometric description data and an index cache is built; Visual attributes are queried based on the status values ​​in the linked events and applied to the target node, supporting interactive filtering; Detect the end signal of the interaction, read the latest data to generate a snapshot of the final state attributes, and restore the visual state of the nodes in batches.

2. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 1, characterized in that, The process of defining the spatial coordinates of the cylinder location and filtering available cylinder locations to generate a standardized candidate list includes: Establish a three-dimensional rectangular coordinate system and assign a unique position code to each cylinder position; Read all cylinder position status information to form a complete cylinder position status set; Based on the full set of cylinder position statuses, occupied, abnormal, and blacklisted cylinder positions are removed to obtain a valid set of available cylinder position candidates. The effective available cylinder candidate set is sorted in ascending order by row number and column number, and a standardized candidate list is output.

3. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 1, characterized in that, Based on the standardized candidate list, a target bobbin position is selected, and the bobbin production data is bound to the target bobbin position and written into storage, including: Target cylinder positions are selected from the standardized candidate list according to a preset allocation mode; Collect yarn bobbin production data and combine it with the target bobbin position and yarn cart number to form a data record; The data record is written into storage using the combination of the yarn car number and the target bobbin position as the primary key; Robot operation instructions are generated and sent based on the target cylinder position and its spatial coordinates.

4. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 1, characterized in that, The listener requests for abnormal status updates, upon successful verification, update the storage and generate a linked event, including: Receive abnormal status update requests and perform correlation checks based on data records; After the verification is successful, the abnormal status field of the corresponding record in the storage will be updated to the new status value; Generate a linkage event that includes the yarn car number, bobbin position code, and new status value based on the updated data snapshot; Write the linked event into the event queue and send an event ready notification.

5. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 1, characterized in that, The response to the linkage event, matching target nodes in the 3D geometric description data and constructing an index cache, includes: Load the 3D geometric description data and parse it to obtain the original list of node names; Based on the cylinder position code in the linkage event, a target node name is generated according to the naming rules and matched in the list of original node names; The successfully matched node references and the tunable codes are written as key-value pairs into an in-memory hash table to build an index cache. Based on the index cache and the data records in storage, perform mapping integrity verification and output valid node references.

6. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 5, characterized in that, Visual attributes are queried based on the state values ​​in the linked events and applied to the target node, supporting interactive filtering, including: Use the new state value in the linked event as an index to query the configuration table to determine the target rendering parameters; Apply the target rendering parameters to the node pointed to by the valid node reference and trigger a local redraw; Receive filtering instructions and calculate node visibility masks based on data records in storage; The node display status is adjusted according to the node visibility mask, and the node can be clicked to query data records in reverse.

7. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 1, characterized in that, The detection of the interaction end signal, reading the latest data to generate a final state attribute snapshot and batch restoring the node visual state includes: When a filter cancellation or view switching signal is detected, the recovery process is triggered and event listening is paused. Reread all data records and generate a set of final state attribute snapshots by querying the configuration table; Iterate through the final state attribute snapshot set and obtain node references from the index cache to apply the final state attributes in batches; Perform a final state consistency check and, upon successful completion, send a recovery completion signal to restart event listening.

8. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 3, characterized in that, Selecting target cell positions from the standardized candidate list according to a preset allocation mode includes: In either sequential allocation mode or row-first allocation mode, the first element in the standardized candidate list is selected as the target cylinder position; In the column-priority allocation mode, the standardized candidate list is rearranged in ascending order of column number and row number, and the first element is selected as the target tube position. If the standardized candidate list is empty, the allocation will be terminated and an alarm message will be generated.

9. The method for visual monitoring of abnormal bobbin positions in chemical fiber filament carts based on a three-dimensional model according to claim 4, characterized in that, Receive abnormal status update requests and perform correlation checks based on data records, including: Check if a record exists in the storage that uses the silk car number and bobbin position code from the request as the primary key; If it exists, further verify whether the spool number in the record matches the spool number provided by the request source; The update process will only be initiated if both checks pass; When verification fails, an exception log is recorded and the exception status update request is discarded.

10. A three-dimensional model-based visual monitoring system for abnormal bobbin positions in chemical fiber filament carts, used to implement the method as described in any one of claims 1-9, characterized in that, include: The candidate set construction unit is used to define the spatial coordinates of the cylinder and filter available cylinders to generate a standardized candidate list. A data binding unit is used to select a target bobbin position based on the standardized candidate list and bind the bobbin production data with the target bobbin position and write it into storage. The event generation unit is used to listen for abnormal status update requests, update the storage and generate linked events after verification; A node mapping unit is used to respond to the linkage event, match target nodes in the three-dimensional geometric description data, and build an index cache; The visual update unit is used to query visual attributes based on the state values ​​in the linkage event and apply them to the target node, supporting interactive filtering. The state recovery unit is used to detect the end signal of the interaction, read the latest data to generate a snapshot of the final state attributes, and restore the visual state of the nodes in batches.

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